So how can the healthcare sector rehabilitate its reputation? It can start by reducing sky-high expenses and inefficiencies, specifically through the careful use of AI. Automating menial, mindless, and mentally grueling tasks will allow administrators streamline their sector in a number of ways, from cracking down on runaway costs to trimming bloated departments.

Why AI is so suitable

If you look closely, you’ll see that AI’s strengths are the perfect foil for the healthcare industry’s shortcomings, which center around excessive paperwork, bureaucracy, and an inability to address mistakes. The strengths of AI are in tracking and crunching reams of data and presenting such information in a simple, easy-to-digest form. Tasks that would take an army of human analysts working nonstop for days could be completed by AI in a matter of hours.

Rather than replacing administrators outright, AI can simply make their jobs easier. The algorithms in use today are narrow AIs: they specialize in a clearly defined niche, and are limited in their functionality. For now, such AIs can gather and interpret data–but when it comes to complex problem solving (like negotiating contracts between insurers and providers or troubleshooting excess financial waste), human intervention is required. Even if computer-generated data inform strategies and action plans, on its own, most AIs can’t easily adapt to complex environments.

AI Can Reduce Wasted Supplies

And there’s little doubt that healthcare is particularly complex, and as a result, very wasteful, especially at facilities such as hospitals or inpatient clinics. In such complicated operations with so many moving parts, perhaps some inefficiency is inevitable.

What is preventable, however, is how much perfectly good equipment and medicine is discarded. In 2017, ProPublica revealed just how many medical supplies were discarded. Reporters visited large warehouses overflowing with unexpired, never-used medical devices and drugs in mint condition. One nonprofit that collects these supplies estimates that they have $20 million worth of supplies in four warehouses.

Therein lies the promise of AI: rather than leaving overworked staff to rummage through supply cabinets and throw out expired and unused stuff alike, AI can track, organize, and maintain stores of medicines and supplies. After all, there are already similar devices for the consumer market, such as smart refrigerators, which can help households order new groceries when they run low, keep tabs on what’s expired and what’s fresh, and so forth.

Obviously, hospitals or inpatient clinics require something more powerful than a residential fridge. But the foundation for this smart technology, known as the Internet of Things (IoT), may hold the key to solving the issue of medical waste. The IoT is basically a network of advanced devices that can collect data through their sensors, share information across the cloud, and finally, apply advanced analytics to glean insights. For example, a human administrator could forget that there is an existing cache of antipsychotics located in a certain storage room (and thus order more). However, a well-maintained IoT interface could help staff track down this extra medicine, saving the money that would have otherwise been wasted in buying redundant supplies.

AI can correct billing mistakes

If we break down the $750 billion annual waste in the American healthcare system, a significant portion comes from back-end problems. A graphic by The Atlanticputs this into perspective: inflated prices, excessive administrative costs, and outright fraud account for a total of 48.3 percent of all unnecessary expenditures.

In fact, my company, Zealie, was born out of my own frustration with the medical billing process. For me, the heart of the problem was inefficiency and confusion: there were countless errors caused either by humans, poor procedures, or lack of adequate technology adoption by all the parties involved. To catch and correct all the errors caused by these issues it took up hours of my staff’s time, and oftentimes they would simply give up on the process due to frustration.

This is especially true if an AI is overseeing a network of IoT devices at a hospital. In this capacity, an AI could track treatment, codes, drugs, dosages, and tests, cross referencing line items with both paper and digital records–often in real time. After all, connected devices constantly submit data to their network; this could take the form of bar codes, or smart cabinets that track the exact type and quantity of each prescription filled. Best of all, unlike humans, an AI biller is less likely to upcode, upcharge, or double bill, simply because it doesn’t make mistakes–nor can it engage in fraud.

Ali Beheshti is the founder and CEO of Zealie, the premier behavioral health Revenue Cycle Management. Ali is passionate about transforming behavioral health by creating influential businesses that uses data, automation, AI, and other emerging technologies to bring innovation and efficiency to the sector.